Remote execution using a global identity

ABSTRACT

Embodiments of the present disclosure may provide a streamlined process for performing operations, such as data sharing and data replication, using multiple accounts. A global identity (also referred to as an organization user) may be employed, where the global identity may have access to multiple accounts across the same or different deployments. The global identity may switch between accounts from its login session and perform various tasks in the context of different accounts without undergoing further authentication.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of U.S. patent application Ser. No.17/345,101, filed Jun. 11, 2021, which is a Continuation of U.S. patentapplication Ser. No. 16/931,808 filed Jul. 17, 2020 and now issued asU.S. Pat. No. 11,057,491, the contents of which are hereby incorporatedby reference herein in their entireties.

TECHNICAL FIELD

The present disclosure generally relates to remote execution of tasksassociated with different accounts.

BACKGROUND

Database and other data processing systems may be implemented indifferent configurations and arrangements. For example, cloud databasesystems may be provided through a cloud platform, which allowsorganizations and users to store, manage, and retrieve data from thecloud. An organization may utilize deployments in different regions inaddition to using different types of deployments. For instance, clouddatabase systems may be implemented as a public deployment, wheremultiple accounts can share processing resources and/or storage. Clouddatabase systems may also be implemented as a private deployment, whereprocessing resources and/or storage are dedicated and isolated.

However, in such systems, performing some operations can be cumbersome.Some operations can include the involvement of multiple accounts. Forexample, an operation may include performing a first task using a firstaccount and then performing a second task using a second account and soon. Thus, a user would have to log into the first account to perform thefirst task, log off, and then log into the second account to perform thesecond task and so on, leading to an inefficient process.

BRIEF DESCRIPTION OF THE DRAWINGS

Various ones of the appended drawings merely illustrate exampleembodiments of the present disclosure and should not be considered aslimiting its scope.

FIG. 1 illustrates an example computing environment in which anetwork-based data warehouse system can implement streams on shareddatabase objects, according to some example embodiments.

FIG. 2 is a block diagram illustrating components of a compute servicemanager, according to some example embodiments.

FIG. 3 is a block diagram illustrating components of an executionplatform, according to some example embodiments.

FIG. 4 is a block diagram illustrating a multiple deploymentenvironment, according to some example embodiments.

FIG. 5 is a block diagram illustrating a relationship tree of a globalidentity, according to some example embodiments.

FIG. 6 is a block diagram illustrating a login session, according tosome example embodiments.

FIG. 7 shows a flow diagram for performing an operation using a globalidentity, according to some example embodiments.

FIG. 8 shows a flow diagram for remote processing, according to someexample embodiments.

FIGS. 9A-9B show a flow diagram for operating a login session, accordingto some example embodiments.

FIG. 10 illustrates a diagrammatic representation of a machine in theform of a computer system within which a set of instructions may beexecuted for causing the machine to perform any one or more of themethodologies discussed herein, in accordance with some embodiments ofthe present disclosure.

DETAILED DESCRIPTION

The description that follows includes systems, methods, techniques,instruction sequences, and computing machine program products thatembody illustrative embodiments of the disclosure. In the followingdescription, for the purposes of explanation, numerous specific detailsare set forth in order to provide an understanding of variousembodiments of the inventive subject matter. It will be evident,however, to those skilled in the art, that embodiments of the inventivesubject matter may be practiced without these specific details. Ingeneral, well-known instruction instances, protocols, structures, andtechniques are not necessarily shown in detail.

Embodiments of the present disclosure may provide a streamlined processfor performing operations, such as data sharing and data replication,using multiple accounts. A global identity (also referred to as anorganization user) may be employed, where the global identity may haveaccess to multiple accounts across the same or different deployments.The global identity may switch between accounts from its login sessionand perform various tasks in the context of different accounts withoutundergoing further authentication. From the user perspective, executionof the tasks may look the same irrespective of which account is used bythe global identity because the login session may be used for all taskexecutions. On the backend, however, remote sessions and proxy users maybe employed to perform tasks using different accounts. Thus, those tasksmay be performed in the context of other accounts from the loginsession.

FIG. 1 illustrates an example shared data processing platform 100, inaccordance with some embodiments of the present disclosure. To avoidobscuring the inventive subject matter with unnecessary detail, variousfunctional components that are not germane to conveying an understandingof the inventive subject matter have been omitted from the figures.However, a skilled artisan will readily recognize that variousadditional functional components may be included as part of the shareddata processing platform 100 to facilitate additional functionality thatis not specifically described herein.

As shown, the shared data processing platform 100 comprises thenetwork-based data warehouse system 102, a cloud computing storageplatform 104 (e.g., a storage platform, an AWS® service, MicrosoftAzure®, or Google Cloud Services®), and a remote computing device 106.The network-based data warehouse system 102 is a network-based systemused for storing and accessing data (e.g., internally storing data,accessing external remotely located data) in an integrated manner, andreporting and analysis of the integrated data from the one or moredisparate sources (e.g., the cloud computing storage platform 104). Thecloud computing storage platform 104 comprises a plurality of computingmachines and provides on-demand computer system resources such as datastorage and computing power to the network-based data warehouse system102. While in the embodiment illustrated in FIG. 1 , a data warehouse isdepicted, other embodiments may include other types of databases orother data processing systems.

The remote computing device 106 (e.g., a user device such as a laptopcomputer) comprises one or more computing machines (e.g., a user devicesuch as a laptop computer) that execute a remote software component 108(e.g., browser accessed cloud service) to provide additionalfunctionality to users of the network-based data warehouse system 102.The remote software component 108 comprises a set of machine-readableinstructions (e.g., code) that, when executed by the remote computingdevice 106, cause the remote computing device 106 to provide certainfunctionality. The remote software component 108 may operate on inputdata and generates result data based on processing, analyzing, orotherwise transforming the input data. As an example, the remotesoftware component 108 can be a data provider or data consumer thatenables database tracking procedures, such as streams on shared tablesand views, as discussed in further detail below.

The network-based data warehouse system 102 comprises an accessmanagement system 110, a compute service manager 112, an executionplatform 114, and a database 116. The access management system 110enables administrative users to manage access to resources and servicesprovided by the network-based data warehouse system 102. Administrativeusers can create and manage users, roles, and groups, and usepermissions to allow or deny access to resources and services. Theaccess management system 110 can store share data that securely managesshared access to the storage resources of the cloud computing storageplatform 104 amongst different users of the network-based data warehousesystem 102, as discussed in further detail below.

The compute service manager 112 coordinates and manages operations ofthe network-based data warehouse system 102. The compute service manager112 also performs query optimization and compilation as well as managingclusters of computing services that provide compute resources (e.g.,virtual warehouses, virtual machines, EC2 clusters). The compute servicemanager 112 can support any number of client accounts such as end usersproviding data storage and retrieval requests, system administratorsmanaging the systems and methods described herein, and othercomponents/devices that interact with compute service manager 112.

The compute service manager 112 is also coupled to database 116, whichis associated with the entirety of data stored on the shared dataprocessing platform 100. The database 116 stores data pertaining tovarious functions and aspects associated with the network-based datawarehouse system 102 and its users.

In some embodiments, database 116 includes a summary of data stored inremote data storage systems as well as data available from one or morelocal caches. Additionally, database 116 may include informationregarding how data is organized in the remote data storage systems andthe local caches. Database 116 allows systems and services to determinewhether a piece of data needs to be accessed without loading oraccessing the actual data from a storage device. The compute servicemanager 112 is further coupled to an execution platform 114, whichprovides multiple computing resources (e.g., virtual warehouses) thatexecute various data storage and data retrieval tasks, as discussed ingreater detail below.

Execution platform 114 is coupled to multiple data storage devices 124-1to 124-n that are part of a cloud computing storage platform 104. Insome embodiments, data storage devices 124-1 to 124-n are cloud-basedstorage devices located in one or more geographic locations. Forexample, data storage devices 124-1 to 124-n may be part of a publiccloud infrastructure or a private cloud infrastructure. Data storagedevices 124-1 to 124-n may be hard disk drives (HDDs), solid statedrives (SSDs), storage clusters, Amazon S3 storage systems or any otherdata storage technology. Additionally, cloud computing storage platform104 may include distributed file systems (such as Hadoop DistributedFile Systems (HDFS)), object storage systems, and the like.

The execution platform 114 comprises a plurality of compute nodes (e.g.,virtual warehouses). A set of processes on a compute node executes aquery plan compiled by the compute service manager 112. The set ofprocesses can include: a first process to execute the query plan; asecond process to monitor and delete micro-partition files using a leastrecently used (LRU) policy, and implement an out of memory (00M) errormitigation process; a third process that extracts health informationfrom process logs and status information to send back to the computeservice manager 112; a fourth process to establish communication withthe compute service manager 112 after a system boot; and a fifth processto handle all communication with a compute cluster for a given jobprovided by the compute service manager 112 and to communicateinformation back to the compute service manager 112 and other computenodes of the execution platform 114.

The cloud computing storage platform 104 also comprises an accessmanagement system 118 and a web proxy 120. As with the access managementsystem 110, the access management system 118 allows users to create andmanage users, roles, and groups, and use permissions to allow or denyaccess to cloud services and resources. The access management system 110of the network-based data warehouse system 102 and the access managementsystem 118 of the cloud computing storage platform 104 can communicateand share information so as to enable access and management of resourcesand services shared by users of both the network-based data warehousesystem 102 and the cloud computing storage platform 104. The web proxy120 handles tasks involved in accepting and processing concurrent APIcalls, including traffic management, authorization and access control,monitoring, and API version management. The web proxy 120 provides HTTPproxy service for creating, publishing, maintaining, securing, andmonitoring APIs (e.g., REST APIs).

In some embodiments, communication links between elements of the shareddata processing platform 100 are implemented via one or more datacommunication networks. These data communication networks may utilizeany communication protocol and any type of communication medium. In someembodiments, the data communication networks are a combination of two ormore data communication networks (or sub-networks) coupled to oneanother. In alternate embodiments, these communication links areimplemented using any type of communication medium and any communicationprotocol.

As shown in FIG. 1 , data storage devices 124-1 to 124-N are decoupledfrom the computing resources associated with the execution platform 114.That is, new virtual warehouses can be created and terminated in theexecution platform 114 and additional data storage devices can becreated and terminated on the cloud computing storage platform 104 in anindependent manner. This architecture supports dynamic changes to thenetwork-based data warehouse system 102 based on the changing datastorage/retrieval needs as well as the changing needs of the users andsystems accessing the shared data processing platform 100. The supportof dynamic changes allows network-based data warehouse system 102 toscale quickly in response to changing demands on the systems andcomponents within network-based data warehouse system 102. Thedecoupling of the computing resources from the data storage devices124-1 to 124-n supports the storage of large amounts of data withoutrequiring a corresponding large amount of computing resources.Similarly, this decoupling of resources supports a significant increasein the computing resources utilized at a particular time withoutrequiring a corresponding increase in the available data storageresources. Additionally, the decoupling of resources enables differentaccounts to handle creating additional compute resources to process datashared by other users without affecting the other users' systems. Forinstance, a data provider may have three compute resources and sharedata with a data consumer, and the data consumer may generate newcompute resources to execute queries against the shared data, where thenew compute resources are managed by the data consumer and do not affector interact with the compute resources of the data provider.

Compute service manager 112, database 116, execution platform 114, cloudcomputing storage platform 104, and remote computing device 106 areshown in FIG. 1 as individual components. However, each of computeservice manager 112, database 116, execution platform 114, cloudcomputing storage platform 104, and remote computing environment may beimplemented as a distributed system (e.g., distributed across multiplesystems/platforms at multiple geographic locations) connected by APIsand access information (e.g., tokens, login data). Additionally, each ofcompute service manager 112, database 116, execution platform 114, andcloud computing storage platform 104 can be scaled up or down(independently of one another) depending on changes to the requestsreceived and the changing needs of shared data processing platform 100.Thus, in the described embodiments, the network-based data warehousesystem 102 is dynamic and supports regular changes to meet the currentdata processing needs.

During typical operation, the network-based data warehouse system 102processes multiple jobs (e.g., queries) determined by the computeservice manager 112. These jobs are scheduled and managed by the computeservice manager 112 to determine when and how to execute the job. Forexample, the compute service manager 112 may divide the job intomultiple discrete tasks and may determine what data is needed to executeeach of the multiple discrete tasks. The compute service manager 112 mayassign each of the multiple discrete tasks to one or more nodes of theexecution platform 114 to process the task. The compute service manager112 may determine what data is needed to process a task and furtherdetermine which nodes within the execution platform 114 are best suitedto process the task. Some nodes may have already cached the data neededto process the task (due to the nodes having recently downloaded thedata from the cloud computing storage platform 104 for a previous job)and, therefore, be a good candidate for processing the task. Metadatastored in the database 116 assists the compute service manager 112 indetermining which nodes in the execution platform 114 have alreadycached at least a portion of the data needed to process the task. One ormore nodes in the execution platform 114 process the task using datacached by the nodes and, if necessary, data retrieved from the cloudcomputing storage platform 104. It is desirable to retrieve as much dataas possible from caches within the execution platform 114 because theretrieval speed is typically much faster than retrieving data from thecloud computing storage platform 104.

As shown in FIG. 1 , the shared data processing platform 100 separatesthe execution platform 114 from the cloud computing storage platform104. In this arrangement, the processing resources and cache resourcesin the execution platform 114 operate independently of the data storagedevices 124-1 to 124-n in the cloud computing storage platform 104.Thus, the computing resources and cache resources are not restricted tospecific data storage devices 124-1 to 124-n. Instead, all computingresources and all cache resources may retrieve data from, and store datato, any of the data storage resources in the cloud computing storageplatform 104.

FIG. 2 is a block diagram illustrating components of the compute servicemanager 112, in accordance with some embodiments of the presentdisclosure. As shown in FIG. 2 , a request processing service 202manages received data storage requests and data retrieval requests(e.g., jobs to be performed on database data). For example, the requestprocessing service 202 may determine the data necessary to process areceived query (e.g., a data storage request or data retrieval request).The data may be stored in a cache within the execution platform 114 orin a data storage device in cloud computing storage platform 104. Amanagement console service 204 supports access to various systems andprocesses by administrators and other system managers. Additionally, themanagement console service 204 may receive a request to execute a joband monitor the workload on the system. The stream share engine 225manages change tracking on database objects, such as a data share (e.g.,shared table) or shared view, according to some example embodiments, andas discussed in further detail below.

The compute service manager 112 also includes a job compiler 206, a joboptimizer 208, and a job executor 210. The job compiler 206 parses a jobinto multiple discrete tasks and generates the execution code for eachof the multiple discrete tasks. The job optimizer 208 determines thebest method to execute the multiple discrete tasks based on the datathat needs to be processed. The job optimizer 208 also handles variousdata pruning operations and other data optimization techniques toimprove the speed and efficiency of executing the job. The job executor210 executes the execution code for jobs received from a queue ordetermined by the compute service manager 112.

A job scheduler and coordinator 212 sends received jobs to theappropriate services or systems for compilation, optimization, anddispatch to the execution platform 114. For example, jobs may beprioritized and processed in that prioritized order. In an embodiment,the job scheduler and coordinator 212 determines a priority for internaljobs that are scheduled by the compute service manager 112 with other“outside” jobs such as user queries that may be scheduled by othersystems in the database but may utilize the same processing resources inthe execution platform 114. In some embodiments, the job scheduler andcoordinator 212 identifies or assigns particular nodes in the executionplatform 114 to process particular tasks. A virtual warehouse manager214 manages the operation of multiple virtual warehouses implemented inthe execution platform 114. As discussed below, each virtual warehouseincludes multiple execution nodes that each include a cache and aprocessor (e.g., a virtual machine, a operating system level containerexecution environment).

Additionally, the compute service manager 112 includes a configurationand metadata manager 216, which manages the information related to thedata stored in the remote data storage devices and in the local caches(i.e., the caches in execution platform 114). The configuration andmetadata manager 216 uses the metadata to determine which datamicro-partitions need to be accessed to retrieve data for processing aparticular task or job. A monitor and workload analyzer 218 overseesprocesses performed by the compute service manager 112 and manages thedistribution of tasks (e.g., workload) across the virtual warehouses andexecution nodes in the execution platform 114. The monitor and workloadanalyzer 218 also redistributes tasks, as needed, based on changingworkloads throughout the network-based data warehouse system 102 and mayfurther redistribute tasks based on a user (e.g., “external”) queryworkload that may also be processed by the execution platform 114. Theconfiguration and metadata manager 216 and the monitor and workloadanalyzer 218 are coupled to a data storage device 220. Data storagedevice 220 in FIG. 2 represent any data storage device within thenetwork-based data warehouse system 102. For example, data storagedevice 220 may represent caches in execution platform 114, storagedevices in cloud computing storage platform 104, or any other storagedevice.

FIG. 3 is a block diagram illustrating components of the executionplatform 114, in accordance with some embodiments of the presentdisclosure. As shown in FIG. 3 , execution platform 114 includesmultiple virtual warehouses, which are elastic clusters of computeinstances, such as virtual machines. In the example illustrated, thevirtual warehouses include virtual warehouse 1, virtual warehouse 2, andvirtual warehouse n. Each virtual warehouse (e.g., EC2 cluster) includesmultiple execution nodes (e.g., virtual machines) that each include adata cache and a processor. The virtual warehouses can execute multipletasks in parallel by using the multiple execution nodes. As discussedherein, execution platform 114 can add new virtual warehouses and dropexisting virtual warehouses in real time based on the current processingneeds of the systems and users. This flexibility allows the executionplatform 114 to quickly deploy large amounts of computing resources whenneeded without being forced to continue paying for those computingresources when they are no longer needed. All virtual warehouses canaccess data from any data storage device (e.g., any storage device incloud computing storage platform 104).

Although each virtual warehouse shown in FIG. 3 includes three executionnodes, a particular virtual warehouse may include any number ofexecution nodes. Further, the number of execution nodes in a virtualwarehouse is dynamic, such that new execution nodes are created whenadditional demand is present, and existing execution nodes are deletedwhen they are no longer necessary (e.g., upon a query or jobcompletion).

Each virtual warehouse is capable of accessing any of the data storagedevices 124-1 to 124-n shown in FIG. 1 . Thus, the virtual warehousesare not necessarily assigned to a specific data storage device 124-1 to124-n and, instead, can access data from any of the data storage devices124-1 to 124-n within the cloud computing storage platform 104.Similarly, each of the execution nodes shown in FIG. 3 can access datafrom any of the data storage devices 124-1 to 124-n. For instance, thestorage device 124-1 of a first user (e.g., provider account user) maybe shared with a worker node in a virtual warehouse of another user(e.g., consumer account user), such that the other user can create adatabase (e.g., read-only database) and use the data in storage device124-1 directly without needing to copy the data (e.g., copy it to a newdisk managed by the consumer account user). In some embodiments, aparticular virtual warehouse or a particular execution node may betemporarily assigned to a specific data storage device, but the virtualwarehouse or execution node may later access data from any other datastorage device.

In the example of FIG. 3 , virtual warehouse 1 includes three executionnodes 302-1, 302-2, and 302-n. Execution node 302-1 includes a cache304-1 and a processor 306-1. Execution node 302-2 includes a cache 304-2and a processor 306-2. Execution node 302-n includes a cache 304-n and aprocessor 306-n. Each execution node 302-1, 302-2, and 302-n isassociated with processing one or more data storage and/or dataretrieval tasks. For example, a virtual warehouse may handle datastorage and data retrieval tasks associated with an internal service,such as a clustering service, a materialized view refresh service, afile compaction service, a storage procedure service, or a file upgradeservice. In other implementations, a particular virtual warehouse mayhandle data storage and data retrieval tasks associated with aparticular data storage system or a particular category of data.

Similar to virtual warehouse 1 discussed above, virtual warehouse 2includes three execution nodes 312-1, 312-2, and 312-n. Execution node312-1 includes a cache 314-1 and a processor 316-1. Execution node 312-2includes a cache 314-2 and a processor 316-2. Execution node 312-nincludes a cache 314-n and a processor 316-n. Additionally, virtualwarehouse 3 includes three execution nodes 322-1, 322-2, and 322-n.Execution node 322-1 includes a cache 324-1 and a processor 326-1.Execution node 322-2 includes a cache 324-2 and a processor 326-2.Execution node 322-n includes a cache 324-n and a processor 326-n.

In some embodiments, the execution nodes shown in FIG. 3 are statelesswith respect to the data the execution nodes are caching. For example,these execution nodes do not store or otherwise maintain stateinformation about the execution node, or the data being cached by aparticular execution node. Thus, in the event of an execution nodefailure, the failed node can be transparently replaced by another node.Since there is no state information associated with the failed executionnode, the new (replacement) execution node can easily replace the failednode without concern for recreating a particular state.

Although the execution nodes shown in FIG. 3 each include one data cacheand one processor, alternative embodiments may include execution nodescontaining any number of processors and any number of caches.Additionally, the caches may vary in size among the different executionnodes. The caches shown in FIG. 3 store, in the local execution node(e.g., local disk), data that was retrieved from one or more datastorage devices in cloud computing storage platform 104 (e.g., S3objects recently accessed by the given node). In some exampleembodiments, the cache stores file headers and individual columns offiles as a query downloads only columns necessary for that query.

To improve cache hits and avoid overlapping redundant data stored in thenode caches, the job optimizer 208 assigns input file sets to the nodesusing a consistent hashing scheme to hash over table file names of thedata accessed (e.g., data in database 116 or database 122). Subsequentor concurrent queries accessing the same table file will therefore beperformed on the same node, according to some example embodiments.

As discussed, the nodes and virtual warehouses may change dynamically inresponse to environmental conditions (e.g., disaster scenarios),hardware/software issues (e.g., malfunctions), or administrative changes(e.g., changing from a large cluster to smaller cluster to lower costs).In some example embodiments, when the set of nodes changes, no data isreshuffled immediately. Instead, the least recently used replacementpolicy is implemented to eventually replace the lost cache contents overmultiple jobs. Thus, the caches reduce or eliminate the bottleneckproblems occurring in platforms that consistently retrieve data fromremote storage systems. Instead of repeatedly accessing data from theremote storage devices, the systems and methods described herein accessdata from the caches in the execution nodes, which is significantlyfaster and avoids the bottleneck problem discussed above. In someembodiments, the caches are implemented using high-speed memory devicesthat provide fast access to the cached data. Each cache can store datafrom any of the storage devices in the cloud computing storage platform104.

Further, the cache resources and computing resources may vary betweendifferent execution nodes. For example, one execution node may containsignificant computing resources and minimal cache resources, making theexecution node useful for tasks that require significant computingresources. Another execution node may contain significant cacheresources and minimal computing resources, making this execution nodeuseful for tasks that require caching of large amounts of data. Yetanother execution node may contain cache resources providing fasterinput-output operations, useful for tasks that require fast scanning oflarge amounts of data. In some embodiments, the execution platform 114implements skew handling to distribute work amongst the cache resourcesand computing resources associated with a particular execution, wherethe distribution may be further based on the expected tasks to beperformed by the execution nodes. For example, an execution node may beassigned more processing resources if the tasks performed by theexecution node become more processor-intensive. Similarly, an executionnode may be assigned more cache resources if the tasks performed by theexecution node require a larger cache capacity. Further, some nodes maybe executing much slower than others due to various issues (e.g.,virtualization issues, network overhead). In some example embodiments,the imbalances are addressed at the scan level using a file stealingscheme. In particular, whenever a node process completes scanning itsset of input files, it requests additional files from other nodes. Ifthe one of the other nodes receives such a request, the node analyzesits own set (e.g., how many files are left in the input file set whenthe request is received), and then transfers ownership of one or more ofthe remaining files for the duration of the current job (e.g., query).The requesting node (e.g., the file stealing node) then receives thedata (e.g., header data) and downloads the files from the cloudcomputing storage platform 104 (e.g., from data storage device 124-1),and does not download the files from the transferring node. In this way,lagging nodes can transfer files via file stealing in a way that doesnot worsen the load on the lagging nodes.

Although virtual warehouses 1, 2, and n are associated with the sameexecution platform 114, the virtual warehouses may be implemented usingmultiple computing systems at multiple geographic locations. Forexample, virtual warehouse 1 can be implemented by a computing system ata first geographic location, while virtual warehouses 2 and n areimplemented by another computing system at a second geographic location.In some embodiments, these different computing systems are cloud-basedcomputing systems maintained by one or more different entities.

Additionally, each virtual warehouse is shown in FIG. 3 as havingmultiple execution nodes. The multiple execution nodes associated witheach virtual warehouse may be implemented using multiple computingsystems at multiple geographic locations. For example, an instance ofvirtual warehouse 1 implements execution nodes 302-1 and 302-2 on onecomputing platform at a geographic location and implements executionnode 302-n at a different computing platform at another geographiclocation. Selecting particular computing systems to implement anexecution node may depend on various factors, such as the level ofresources needed for a particular execution node (e.g., processingresource requirements and cache requirements), the resources availableat particular computing systems, communication capabilities of networkswithin a geographic location or between geographic locations, and whichcomputing systems are already implementing other execution nodes in thevirtual warehouse.

Execution platform 114 is also fault tolerant. For example, if onevirtual warehouse fails, that virtual warehouse is quickly replaced witha different virtual warehouse at a different geographic location.

A particular execution platform 114 may include any number of virtualwarehouses. Additionally, the number of virtual warehouses in aparticular execution platform is dynamic, such that new virtualwarehouses are created when additional processing and/or cachingresources are needed. Similarly, existing virtual warehouses may bedeleted when the resources associated with the virtual warehouse are nolonger necessary.

In some embodiments, the virtual warehouses may operate on the same datain cloud computing storage platform 104, but each virtual warehouse hasits own execution nodes with independent processing and cachingresources. This configuration allows requests on different virtualwarehouses to be processed independently and with no interferencebetween the requests. This independent processing, combined with theability to dynamically add and remove virtual warehouses, supports theaddition of new processing capacity for new users without impacting theperformance observed by the existing users.

FIG. 4 shows an example multiple deployment environment, according tosome example embodiments. A deployment may include multiple componentssuch as a metadata store, a front-end layer, a load balancing layer, adata warehouse, etc., as discussed above with respect to FIGS. 1-3 . Themultiple deployment environment may be provided for one or moreorganizations and may include a plurality of public and privatedeployments. A public deployment may be implemented as a multi-tenantenvironment, where each tenant or account shares processing and/orstorage resources. For example, in a public deployment, multipleaccounts may share a metadata store, a front-end layer, a load balancinglayer, a data warehouse, etc. A private deployment, on the other hand,may be implemented as a dedicated, isolated environment, whereprocessing and/or storage resources may be dedicated. Thus, privatedeployments may offer better security as well as better performance insome configurations.

In FIG. 4 , a private deployment 1 (PRD1) 410 may be provided in cloudprovider region A, and a public deployment 1 (PUD1) 420 may also beprovided in cloud provider region A. A private deployment 2 (PRD2) 430may be provided in another cloud provider region B, and a publicdeployment 2 (PUD2) 440 may also be provided in cloud provider region B.The cloud provider regions A and B may be different geographic regions,for example.

In this example, the different deployments 410, 420, 430, 440 areconfigured to communicate with each other. For example, they can eachsend/receive messages to/from each other in a global messaging layer. Todo so, each deployment may include deployment objects corresponding tothe other communicatively coupled deployments, representing links to thetarget deployments. For example, PRD1 410 may include a PUD1 deploymentobject 412, a PUD2 deployment object 414, and a PRD2 deployment object416. PUD1 420 may include a PRD1 deployment object 422, a PRD2deployment object 424, and a PUD2 deployment object 426. PRD2 430 mayinclude a PRD1 deployment object 432, a PUD1 deployment object 434, anda PUD2 deployment object 436. PUD2 440 may include a PRD1 deploymentobject 442, a PUD1 deployment object 444, and a PRD2 deployment object446. In an embodiment, communication between deployments may beperformed using a metadata store. For example, one deployment may writea message to the metadata store, and another deployment may read thatmessage from the metadata store.

Moreover, each deployment may have different accounts associated withit. For example, PRD1 410 may have Accounts A-F associated with it; PUD1420 may have Accounts G-L associated with it; PRD2 430 may have AccountsM-R associated with it; and PUD2 440 may have Accounts S-X associatedwith it. Certain operations, such as replicating data or sharing data,may involve tasks to be performed by different accounts in the samedeployment or different deployments.

Global identities (also referred to as organization users) and remoteprocessing, as described herein, may be utilized to streamlineperformance of such operations. A global identity may be an identitythat may be known and have access to multiple accounts. The accounts maybe within an organization and may be associated with the same deploymentor different deployments.

FIG. 5 shows an example relationship of a global identity (GI 1) 502,according to some example embodiments. The global identity (GI 1) 502may be associated with multiple selected accounts and is able to accessthose accounts without further authentication. Once a global identity isauthenticated, it may access different accounts associated with thatglobal identity and perform tasks in the context of those accountswithout providing further authentication for those different accounts.That is because the global identity may be authenticated using a globalauthentication mechanism, which is an authentication mechanism that istrusted across an organization. The global authentication mechanism maycreate a one-way trust relationship (also referred to as trusting domainor trusted domain) in which organization accounts may trust an identityassertion made by the global authentication mechanism. As such, eachmapped account may allow the execution of tasks and statements withoutfurther authentication based on the trusted identity assertion from theglobal authentication mechanism.

GI 1 502 may be mapped to different accounts across differentdeployments, cloud providers, and/or regions. For example, referringback to the accounts of FIG. 4 , GI 1 502 may be mapped to Accounts Aand B from PRD1 410, Accounts G and H from PUD1 420, Accounts M and Nfrom PRD2 430, and Accounts S and T from PUD2 440. The mapped accountsfor a global identity may be set by an administrator, who is a userauthorized to manage organization-level entities and metadata.Additionally or alternatively, the mapped accounts for a global identitymay be set based on a set of policy rules. For example, policy rules maybe set so that certain type(s) of accounts are automatically mapped tocertain global identities. For example, a policy rule may automaticallymap all development type accounts in an organization to a select globalidentity, regardless of the region or deployment. Thus, a user may login as the selected global identity, may have access to all developmentaccounts in the organization and may perform tasks in the context of anyof those development accounts. Moreover, if a new development account iscreated within that organization, that new development account may beautomatically mapped to the selected global identity.

After a global identity is authenticated, a login session may beestablished. For example, the login session may be associated with anaccount and a user ID. The login session may provide access to themapped accounts associated with the global identity. FIG. 6 shows alogin session 600 of a global identity, according to some exampleembodiments. The login session 600 may provide information about themapped accounts 602.

Next, different actions able to be performed by the global identity aredescribed. FIG. 7 shows a flow diagram of a method 700 for performing anoperation using a global identity, according to some exampleembodiments. At operation 705, login information for a user in anorganization may be received. The login information may be associatedwith a global identity as defined by the organization. At operation 710,the login information for the global identity (or organization user) maybe authenticated using a global authentication mechanism, as describedherein. For example, a two-factor authentication may be employed forauthenticating a global identity. At operation 715, a login session maybe established. The login session may provide access to the mappedaccounts for the global identity without further authentication. Thatis, the user may access and perform tasks in the context of the mappedaccounts without having to provide further authentications for thoseaccounts because of the trust relationship established by the globalauthentication mechanism.

At operation 720, from the login session, a first task may be performedin the context of a first mapped account from the set of mapped accountsof the global identity. As explained in further detail below, remoteprocessing may be employed to execute the first task by the deploymentassociated with the first account.

At operation 725, also from the login session, a second task may beperformed in the context of a second mapped account from the set ofmapped accounts of the global identity. As explained in further detailbelow, remote processing may be employed to execute the second task bythe deployment associated with the second account. In an embodiment, thedeployments associated with the first and second accounts may be thesame deployment or different deployments. Therefore, a single user mayperform multiple tasks using different accounts from a single loginsession. Thus, global identities and remote processing provide astreamlined interface for a user to perform multiple tasks acrossdifferent accounts.

In an embodiment, the different tasks may be part of a larger operation,such as data replication or data sharing. For example, using a globalidentity, a database may be replicated using a single login session.First, using a first mapped account of the global identity, a masterdatabase may be created and replication of that database may be enabled.Next, using a second mapped account of the global identity, a databasemay be created, linked to the master database so that it is a copy ofthe master database.

The above description primarily focuses on the frontend (e.g., what theuser sees). Next, the backend operations are described. From the loginsession, an organization user may request execution of some statementsto be performed in the context of a mapped account. In the backend, thismay be done by using a “use account” statement, which may indicate tothe login session that subsequent statements should be executed in thecontext of the identified account. A remote session may be created andthen used to execute those subsequent statements. The remote session maybe a persistent session. Remote sessions may be maintained by a sessionpool, which stores information regarding active remote sessions. Remotesessions may be provided in parallel in the session pool of the loginsession so that users may switch from one account to another.

FIG. 8 shows a flow diagram of a method 800 for remote processing,according to some example embodiments. Method 800 may be performed afterauthentication of a global identity and the establishment of a loginsession, as described above. At operation 805, an instruction from theorganization user (logged in as the global identity) is received in alogin session at a source deployment (e.g., a global service (GS)). Theinstruction may include a command or statement of execution associatedwith one of the mapped accounts (e.g., Account A). For example, theinstruction may be a SQL statement.

At operation 810, the source deployment may transmit a request toestablish a remote session to deployment associated with Account A. Thetarget deployment may be the same as the source deployment or may be adifferent deployment. The remote session may refer to remote in thecontext of using another account. The request may be sent over theglobal messaging layer. The request may include one or more parameters,including an account name (for the organization user), the organizationusername, session parameters, and/or an authentication token. Theauthentication token may be a single sign-on (SSO) token to verify theidentity of the organization user.

At operation 815, the deployment associated with Account A may receivethe request and may establish a remote session. The remote session maybe given a remote session ID. The deployment associated with Account Amay also establish a proxy user associated with the organization user.The proxy user may behave like a local user of the deployment. In anembodiment, the username for the proxy user may be the username of theorganization user. However, at least one property value may beassociated with the proxy user that indicates that the proxy user isstanding in for the organization user.

At operation 820, the deployment associated with Account A may transmitconfirmation to the source deployment regarding the establishment of theremote session. The confirmation may include the status of the remotesession (e.g., established/failed) and the remote session ID. Atoperation 825, the remote session ID may be stored in a session poolassociated with the login session. The session pool may maintain dataregarding the set of remote sessions that have been established for thelogin session. For example, the session pool may include informationregarding other remote sessions associated with other mapped accounts.The session pool may be maintained at the backend, and the user may beunaware of it.

At operation 830, the source deployment may transmit an executionrequest to the deployment associated with Account A. For example, theexecution request may include a request to execute a statement and/orquery execution task. The request may include one or more parameters,including the remote session ID and the statement/execution task ID.

At operation 835, in response to receiving the execution request, thedeployment associated with Account A may use the established remotesession and proxy user to execute the request. If the executiongenerates results, those result sets may be stored, for example, in acloud storage.

At operation 840, the deployment associated with Account may send aresponse to the execution request to the source deployment. The responsemay include or be indicative of the results of the execution. For anexecution statement example, the response may include a status (e.g.,started/failed), and an execution task ID. For a query execution task,the response may include task status (e.g., in-progress/completed), atask return code, and a task result set ID. The task result set ID maybe used to retrieve the result set, for example, from the cloud storage.

Additional remote sessions may be established for the other mappedaccounts of the global identity and other tasks may be executed on thoseestablished remote sessions based on requests by the user. Informationregarding those remote sessions may be stored and maintained in thesession pool of the login session. For example, operations 805-840 maybe performed to initially establish a remote session and execute a firsttask in that remote session. Moreover, once a remote session isestablished, other tasks may be executed using that remote session byretrieving information from the session pool. For example, foradditional tasks associated with an established remote session,operations 825-840 may be performed.

In an embodiment, the organization user may cancel an execution task.For example, in response to an instruction to cancel an execution taskfrom the organization user, the source deployment may transmit acancellation request to the deployment associated with the account beingused for execution. The cancellation request may include one or moreparameters, including the remote session ID and the execution task ID.In response to the cancellation request, the deployment may use theidentified remote session to cancel the identified execution task. Thedeployment may transmit a response, which may include a status of therequest (e.g., cancelled/failure). In another embodiment, no responsemay be sent in response to the cancellation request.

The user may also create/use session-local state information, such astemporary tables, session variables, session parameters, etc. Forexample, a user may create one or more temporary tables during the loginsession. These temporary tables may be available for the duration of thelogin session. The temporary tables may be created in the login session(e.g., for tasks performed locally) and/or in remote sessions. Thetemporary tables may be seen by the organization user even as thebackend may switch from account to account. The use of session pools tore-use already established remote sessions for other tasks whenswitching between different mapped accounts that were previously usedmay ensure that temporary tables created in a remote session willcontinue to exist for the duration of the login session.

Consistency may be maintained between the login session and the one ormore remote sessions in the session pool. Session state information maybe maintained across the different remote sessions. This may includesession parameter information and also state information, such as queryresults, such that they are available across the different sessions. Forexample, changes made to the login session may be replicated to allactive remote sessions in the session pool. An alter session may beexecuted in the login session and may also be sent to each active remotesession for execution as well so that all remote sessions may reflectthe indicated change in the alter session command. Moreover, new remotesessions established after the alter session command may be establishedand initialized in a way to reflect the alter session command.

A login session may maintain an established remote session as active inthe session pool. In an embodiment, the login session may performrefresh operations to maintain the established remote session active. Inan embodiment, a remote session may time out and may be removed from thelist of active sessions in the session pool.

A remote session may be terminated. For example, the login session maywish to terminate a remote session. To terminate a remote session, thelogin session may transmit a termination request to the deploymentassociated with the account being used for execution. The terminationrequest may include one or more parameters, including the remote sessionID. In response to the termination request, the deployment may terminatethe remote session. The deployment may transmit a response, which mayinclude a status of the request (e.g., terminated/failure). In anotherembodiment, no response may be sent in response to the terminationrequest.

Moreover, all active remote sessions may be terminated at thetermination of the login session. The login session may transmittermination requests to all active remote sessions at its owntermination.

FIGS. 9A-9B illustrate a flow diagram of a method 900 for operating alogin session for an organization user, according to some exampleembodiments. At operation 902, the user issues a request to connect toan account (CONNECT acct 1), and the source deployment may receive therequest and authenticate the user credentials. The source deployment mayauthenticate the user as an organization user (global identity) using aglobal authentication mechanism, as described herein.

At operation 904, a login session may be created for “acct 1.” Since thelogin session is just created, there may be no active remote sessions.Hence, the value for remote session is set to null,“remote_session=null,” and the session pool is empty“session_pool”=<empty pool.” At operation 906, the user may submit astatement for execution, such as a SQL statement. At operation 908, thestatement may be parsed to create a parse tree.

Next, the source deployment may determine a task associated with thestatement. In operation 910, the source deployment may check if thestatement includes a request to disconnect or terminate the loginsession, “DISCONNECT.” At operation 912, if the statement includes arequest to disconnect/terminate, the login session may send adisconnect/terminate request to every remote session, if any, in thesession pool. At operation 914, the login session may be terminated anda cleanup operation may be performed. For example, the cleanup operationmay include deleting any temporary tables created during the loginsession, as described herein.

If the statement does not include a request to disconnect/terminate, thesource deployment may check if the statement includes a request to use amapped account of the global identity, “USE ACCOUNT,” at operation 916.At operation 918, if the statement includes a “use account” request, thelogin session checks if the target account is the login session account,e.g., acct 1. At operation 920, if the target account is the loginsession account, the remote session register may be set to null(login_session.remote_session=null). The method 900 may then move on tothe next user statement (e.g., operation 906). If however, the targetaccount is not the login session account, the login session may thencheck if the target account is already in the session pool at operation922. At operation 924, if the target account is already in the sessionpool (and therefore may have a remote session ID),login_session.remote_session may set to the target account(“session_pool[target]”). The method 900 may then move on to the nextuser statement (e.g., operation 906).

If the target account is not in the session pool, a new remote sessionmay be created for the target account at operation 926, as describedherein. At operation 928, the “session_pool[target]” register may thenbe set to the newly created remote session, and then method 900 mayproceed to operation 924.

If the statement does not include a request to use account request(operation 916), the source deployment may check if the statementincludes a request to alter the login session, “ALTER SESSION,” atoperation 930. At operation 932, if the statement includes a request toalter the login session, a local execution task may be created toexecute the alter session request. At operation 934, a proxy task foreach active remote session in the session may be created so that allactive remote sessions are modified based on the alter session request.

If the statement does not include an alter session request, the sourcedeployment may then determine the request is for the execution of atask, so the login session may check if the task is for the loginsession or a remote session by checking the value of the“login_session.remote_session” at operation 936. If that register isnull (e.g., the task is for the login session), a local execution taskmay be created for the statement at operation 938. If the register isnot null, a proxy task may be created for the identified remote sessionat operation 940. The method 900 may then move on to the next userstatement (e.g., operation 906).

FIG. 10 illustrates a diagrammatic representation of a machine 1000 inthe form of a computer system within which a set of instructions may beexecuted for causing the machine 1000 to perform any one or more of themethodologies discussed herein, according to an example embodiment.Specifically, FIG. 10 shows a diagrammatic representation of the machine1000 in the example form of a computer system, within which instructions1016 (e.g., software, a program, an application, an applet, an app, orother executable code) for causing the machine 1000 to perform any oneor more of the methodologies discussed herein may be executed. Forexample, the instructions 1016 may cause the machine 1000 to execute anyone or more operations described herein. As another example, theinstructions 1016 may cause the machine 1000 to implemented portions ofthe data flows described herein. In this way, the instructions 1016transform a general, non-programmed machine into a particular machine1000 (e.g., the remote computing device 106, the access managementsystem 110, the compute service manager 112, the execution platform 114,the access management system 118, the Web proxy 120, remote computingdevice 106) that is specially configured to carry out any one of thedescribed and illustrated functions in the manner described herein.

In alternative embodiments, the machine 1000 operates as a standalonedevice or may be coupled (e.g., networked) to other machines. In anetworked deployment, the machine 1000 may operate in the capacity of aserver machine or a client machine in a server-client networkenvironment, or as a peer machine in a peer-to-peer (or distributed)network environment. The machine 1000 may comprise, but not be limitedto, a server computer, a client computer, a personal computer (PC), atablet computer, a laptop computer, a netbook, a smart phone, a mobiledevice, a network router, a network switch, a network bridge, or anymachine capable of executing the instructions 1016, sequentially orotherwise, that specify actions to be taken by the machine 1000.Further, while only a single machine 1000 is illustrated, the term“machine” shall also be taken to include a collection of machines 1000that individually or jointly execute the instructions 1016 to performany one or more of the methodologies discussed herein.

The machine 1000 includes processors 1010, memory 1030, and input/output(I/O) components 1050 configured to communicate with each other such asvia a bus 1002. In an example embodiment, the processors 1010 (e.g., acentral processing unit (CPU), a reduced instruction set computing(RISC) processor, a complex instruction set computing (CISC) processor,a graphics processing unit (GPU), a digital signal processor (DSP), anapplication-specific integrated circuit (ASIC), a radio-frequencyintegrated circuit (RFIC), another processor, or any suitablecombination thereof) may include, for example, a processor 1012 and aprocessor 1014 that may execute the instructions 1016. The term“processor” is intended to include multi-core processors 1010 that maycomprise two or more independent processors (sometimes referred to as“cores”) that may execute instructions 1016 contemporaneously. AlthoughFIG. 10 shows multiple processors 1010, the machine 1000 may include asingle processor with a single core, a single processor with multiplecores (e.g., a multi-core processor), multiple processors with a singlecore, multiple processors with multiple cores, or any combinationthereof.

The memory 1030 may include a main memory 1032, a static memory 1034,and a storage unit 1036, all accessible to the processors 1010 such asvia the bus 1002. The main memory 1032, the static memory 1034, and thestorage unit 1036 store the instructions 1016 embodying any one or moreof the methodologies or functions described herein. The instructions1016 may also reside, completely or partially, within the main memory1032, within the static memory 1034, within the storage unit 1036,within at least one of the processors 1010 (e.g., within the processor'scache memory), or any suitable combination thereof, during executionthereof by the machine 1000.

The I/O components 1050 include components to receive input, provideoutput, produce output, transmit information, exchange information,capture measurements, and so on. The specific I/O components 1050 thatare included in a particular machine 1000 will depend on the type ofmachine. For example, portable machines such as mobile phones willlikely include a touch input device or other such input mechanisms,while a headless server machine will likely not include such a touchinput device. It will be appreciated that the I/O components 1050 mayinclude many other components that are not shown in FIG. 10 . The I/Ocomponents 1050 are grouped according to functionality merely forsimplifying the following discussion and the grouping is in no waylimiting. In various example embodiments, the I/O components 1050 mayinclude output components 1052 and input components 1054. The outputcomponents 1052 may include visual components (e.g., a display such as aplasma display panel (PDP), a light emitting diode (LED) display, aliquid crystal display (LCD), a projector, or a cathode ray tube (CRT)),acoustic components (e.g., speakers), other signal generators, and soforth. The input components 1054 may include alphanumeric inputcomponents (e.g., a keyboard, a touch screen configured to receivealphanumeric input, a photo-optical keyboard, or other alphanumericinput components), point-based input components (e.g., a mouse, atouchpad, a trackball, a joystick, a motion sensor, or another pointinginstrument), tactile input components (e.g., a physical button, a touchscreen that provides location and/or force of touches or touch gestures,or other tactile input components), audio input components (e.g., amicrophone), and the like.

Communication may be implemented using a wide variety of technologies.The I/O components 1050 may include communication components 1064operable to couple the machine 1000 to a network 1080 or devices 1070via a coupling 1082 and a coupling 1072, respectively. For example, thecommunication components 1064 may include a network interface componentor another suitable device to interface with the network 1080. Infurther examples, the communication components 1064 may include wiredcommunication components, wireless communication components, cellularcommunication components, and other communication components to providecommunication via other modalities. The devices 1070 may be anothermachine or any of a wide variety of peripheral devices (e.g., aperipheral device coupled via a universal serial bus (USB)). Forexample, as noted above, the machine 1000 may correspond to any one ofthe remote computing device 106, the access management system 110, thecompute service manager 112, the execution platform 114, the accessmanagement system 118, the Web proxy 120, and the devices 1070 mayinclude any other of these systems and devices.

The various memories (e.g., 1030, 1032, 1034, and/or memory of theprocessor(s) 1010 and/or the storage unit 1036) may store one or moresets of instructions 1016 and data structures (e.g., software) embodyingor utilized by any one or more of the methodologies or functionsdescribed herein. These instructions 1016, when executed by theprocessor(s) 1010, cause various operations to implement the disclosedembodiments.

As used herein, the terms “machine-storage medium,” “device-storagemedium,” and “computer-storage medium” mean the same thing and may beused interchangeably in this disclosure. The terms refer to a single ormultiple storage devices and/or media (e.g., a centralized ordistributed database, and/or associated caches and servers) that storeexecutable instructions and/or data. The terms shall accordingly betaken to include, but not be limited to, solid-state memories, andoptical and magnetic media, including memory internal or external toprocessors. Specific examples of machine-storage media, computer-storagemedia, and/or device-storage media include non-volatile memory,including by way of example semiconductor memory devices, e.g., erasableprogrammable read-only memory (EPROM), electrically erasableprogrammable read-only memory (EEPROM), field-programmable gate arrays(FPGAs), and flash memory devices; magnetic disks such as internal harddisks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROMdisks. The terms “machine-storage media,” “computer-storage media,” and“device-storage media” specifically exclude carrier waves, modulateddata signals, and other such media, at least some of which are coveredunder the term “signal medium” discussed below.

In various example embodiments, one or more portions of the network 1080may be an ad hoc network, an intranet, an extranet, a virtual privatenetwork (VPN), a local-area network (LAN), a wireless LAN (WLAN), awide-area network (WAN), a wireless WAN (WWAN), a metropolitan-areanetwork (MAN), the Internet, a portion of the Internet, a portion of thepublic switched telephone network (PSTN), a plain old telephone service(POTS) network, a cellular telephone network, a wireless network, aWi-Fi® network, another type of network, or a combination of two or moresuch networks. For example, the network 1080 or a portion of the network1080 may include a wireless or cellular network, and the coupling 1082may be a Code Division Multiple Access (CDMA) connection, a GlobalSystem for Mobile communications (GSM) connection, or another type ofcellular or wireless coupling. In this example, the coupling 1082 mayimplement any of a variety of types of data transfer technology, such asSingle Carrier Radio Transmission Technology (1×RTT), Evolution-DataOptimized (EVDO) technology, General Packet Radio Service (GPRS)technology, Enhanced Data rates for GSM Evolution (EDGE) technology,third Generation Partnership Project (3GPP) including 3G, fourthgeneration wireless (4G) networks, Universal Mobile TelecommunicationsSystem (UMTS), High-Speed Packet Access (HSPA), WorldwideInteroperability for Microwave Access (WiMAX), Long Term Evolution (LTE)standard, others defined by various standard-setting organizations,other long-range protocols, or other data transfer technology.

The instructions 1016 may be transmitted or received over the network1080 using a transmission medium via a network interface device (e.g., anetwork interface component included in the communication components1064) and utilizing any one of a number of well-known transfer protocols(e.g., hypertext transfer protocol (HTTP)). Similarly, the instructions1016 may be transmitted or received using a transmission medium via thecoupling 1072 (e.g., a peer-to-peer coupling) to the devices 1070. Theterms “transmission medium” and “signal medium” mean the same thing andmay be used interchangeably in this disclosure. The terms “transmissionmedium” and “signal medium” shall be taken to include any intangiblemedium that is capable of storing, encoding, or carrying theinstructions 1016 for execution by the machine 1000, and include digitalor analog communications signals or other intangible media to facilitatecommunication of such software. Hence, the terms “transmission medium”and “signal medium” shall be taken to include any form of modulated datasignal, carrier wave, and so forth. The term “modulated data signal”means a signal that has one or more of its characteristics set orchanged in such a manner as to encode information in the signal.

The terms “machine-readable medium,” “computer-readable medium,” and“device-readable medium” mean the same thing and may be usedinterchangeably in this disclosure. The terms are defined to includeboth machine-storage media and transmission media. Thus, the termsinclude both storage devices/media and carrier waves/modulated datasignals.

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Similarly, the methods described hereinmay be at least partially processor-implemented. For example, at leastsome of the operations of the methods described herein may be performedby one or more processors. The performance of certain of the operationsmay be distributed among the one or more processors, not only residingwithin a single machine, but also deployed across a number of machines.In some example embodiments, the processor or processors may be locatedin a single location (e.g., within a home environment, an officeenvironment, or a server farm), while in other embodiments theprocessors may be distributed across a number of locations.

Although the embodiments of the present disclosure have been describedwith reference to specific example embodiments, it will be evident thatvarious modifications and changes may be made to these embodimentswithout departing from the broader scope of the inventive subjectmatter. Accordingly, the specification and drawings are to be regardedin an illustrative rather than a restrictive sense. The accompanyingdrawings that form a part hereof show, by way of illustration, and notof limitation, specific embodiments in which the subject matter may bepracticed. The embodiments illustrated are described in sufficientdetail to enable those skilled in the art to practice the teachingsdisclosed herein. Other embodiments may be used and derived therefrom,such that structural and logical substitutions and changes may be madewithout departing from the scope of this disclosure. This DetailedDescription, therefore, is not to be taken in a limiting sense, and thescope of various embodiments is defined only by the appended claims,along with the full range of equivalents to which such claims areentitled.

Such embodiments of the inventive subject matter may be referred toherein, individually and/or collectively, by the term “invention” merelyfor convenience and without intending to voluntarily limit the scope ofthis application to any single invention or inventive concept if morethan one is in fact disclosed. Thus, although specific embodiments havebeen illustrated and described herein, it should be appreciated that anyarrangement calculated to achieve the same purpose may be substitutedfor the specific embodiments shown. This disclosure is intended to coverany and all adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent, to those of skill inthe art, upon reviewing the above description.

In this document, the terms “a” or “an” are used, as is common in patentdocuments, to include one or more than one, independent of any otherinstances or usages of “at least one” or “one or more.” In thisdocument, the term “or” is used to refer to a nonexclusive or, such that“A or B” includes “A but not B,” “B but not A,” and “A and B,” unlessotherwise indicated. In the appended claims, the terms “including” and“in which” are used as the plain-English equivalents of the respectiveterms “comprising” and “wherein.” Also, in the following claims, theterms “including” and “comprising” are open-ended; that is, a system,device, article, or process that includes elements in addition to thoselisted after such a term in a claim is still deemed to fall within thescope of that claim.

The following numbered examples are embodiments:

Example 1. A method comprising: receiving, by one or more processors,login information for a global identity; based on the login information,authenticating the global identity; establishing a login sessionproviding access to a plurality of accounts; from the login session,performing a first task using a first account from the plurality ofaccounts; and from the login session, performing a second task using asecond account from the plurality of accounts.

Example 2. The method of example 1, wherein the login session providesaccess to the plurality of accounts without further authentication.

Example 3. The method of any of examples 1-2, wherein performing thefirst task using the first account comprises: establishing a remotesession with a deployment associated with the first account;transmitting a request to execute the first task to the deploymentassociated with the first account, wherein the task is executed in theremote session generating a result; and receiving the result.

Example 4. The method of any of examples 1-3, further comprising:creating a proxy user for the remote session, the proxy user beingassociated with the global identity.

Example 5. The method of any of examples 1-4, further comprising:establishing a second remote session with a deployment associated withthe second account; transmitting a second request to execute the secondtask to the deployment associated with the second account, wherein thetask is executed in the second remote session generating a secondresult; and receiving the second result.

Example 6. The method of any of examples 1-5, further comprising:providing a session pool of active remote sessions in parallel allowingswitching by the global identity between the active remote sessions.

Example 7. The method of any of examples 1-6, wherein the plurality ofaccounts are selected based on a policy rule related to type ofaccounts.

Example 8. The method of any of examples 1-7, wherein the first accountis associated with a first deployment and the second account isassociated with a second deployment.

Example 9. The method of any of examples 1-8, further comprising:creating a table associated with the login session; and in response tothe login session being terminated, deleting the table.

Example 10. A system comprising: one or more processors of a machine;and a memory storing instructions that, when executed by the one or moreprocessors, cause the machine to perform operations implementing any oneof example methods 1 to 9.

Example 11. A machine-readable storage device embodying instructionsthat, when executed by a machine, cause the machine to performoperations implementing any one of example methods 1 to 9.

What is claimed is:
 1. A method comprising: establishing a login sessionfor a global identity providing access to a plurality of accountsassociated with an organization; from the login session: transmitting afirst request to establish a first remote session with a firstdeployment, the first deployment being associated with a first accountfrom the plurality of accounts; receiving a first confirmation messagefrom the first deployment regarding establishing the first remotesession including a first remote session identification; transmitting afirst execution request to the first deployment to execute a first task,the first execution request including the first remote sessionidentification; receiving a first result in response to the firstexecution request, the first result being generated in the firstdeployment using a first proxy user associated with the global identity;transmitting a second request to establish a second remote session witha second deployment, the second deployment being associated with asecond account from the plurality of accounts; receiving a secondconfirmation message from the second deployment regarding establishingthe second remote session including a second remote sessionidentification; transmitting a second execution request to the seconddeployment to execute a second task, the second execution requestincluding the second remote session identification; and receiving asecond result in response to the second execution request, the secondresult being generated in the second deployment using a second proxyuser associated with the global identity.
 2. The method of claim 1,further comprising: combining the first and second results to generate afinal result.
 3. The method of claim 1, further comprising:authenticating a one-way trust relationship associated with the globalidentity, wherein the single login session provides access to theplurality of accounts without further authentication.
 4. The method ofclaim 3, wherein the authenticating is performed using a single sign-ontoken.
 5. The method of claim 1, further comprising: providing a sessionpool of active remote sessions in parallel allowing switching by theglobal identity between the active remote sessions.
 6. The method ofclaim 1, wherein at least one property value of the first proxy userindicates that that the first proxy user is standing in for the globalidentity.
 7. The method of claim 1, wherein receiving the first resultincludes retrieving the first result from a cloud storage location.
 8. Asystem comprising: one or more processors of a machine; and at least onememory storing instructions that, when executed by the one or moreprocessors, cause the machine to perform operations comprising:establishing a login session for a global identity providing access to aplurality of accounts associated with an organization; from the loginsession: transmitting a first request to establish a first remotesession with a first deployment, the first deployment being associatedwith a first account from the plurality of accounts; receiving a firstconfirmation message from the first deployment regarding establishingthe first remote session including a first remote sessionidentification; transmitting a first execution request to the firstdeployment to execute a first task, the first execution requestincluding the first remote session identification; receiving a firstresult in response to the first execution request, the first resultbeing generated in the first deployment using a first proxy userassociated with the global identity; transmitting a second request toestablish a second remote session with a second deployment, the seconddeployment being associated with a second account from the plurality ofaccounts; receiving a second confirmation message from the seconddeployment regarding establishing the second remote session including asecond remote session identification; transmitting a second executionrequest to the second deployment to execute a second task, the secondexecution request including the second remote session identification;and receiving a second result in response to the second executionrequest, the second result being generated in the second deploymentusing a second proxy user associated with the global identity.
 9. Thesystem of claim 8, the operations further comprising: combining thefirst and second results to generate a final result.
 10. The system ofclaim 8, the operations further comprising: authenticating a one-waytrust relationship associated with the global identity, wherein thesingle login session provides access to the plurality of accountswithout further authentication.
 11. The system of claim 10, wherein theauthenticating is performed using a single sign-on token.
 12. The systemof claim 8, the operations further comprising: providing a session poolof active remote sessions in parallel allowing switching by the globalidentity between the active remote sessions.
 13. The system of claim 8,wherein at least one property value of the first proxy user indicatesthat that the first proxy user is standing in for the global identity.14. The system of claim 8, wherein receiving the first result includesretrieving the first result from a cloud storage location.
 15. Anon-transitory computer readable storage media storing instructionsthat, when executed by one or more processors, cause the one or moreprocessors to: establishing a login session for a global identityproviding access to a plurality of accounts associated with anorganization; from the login session: transmitting a first request toestablish a first remote session with a first deployment, the firstdeployment being associated with a first account from the plurality ofaccounts; receiving a first confirmation message from the firstdeployment regarding establishing the first remote session including afirst remote session identification; transmitting a first executionrequest to the first deployment to execute a first task, the firstexecution request including the first remote session identification;receiving a first result in response to the first execution request, thefirst result being generated in the first deployment using a first proxyuser associated with the global identity; transmitting a second requestto establish a second remote session with a second deployment, thesecond deployment being associated with a second account from theplurality of accounts; receiving a second confirmation message from thesecond deployment regarding establishing the second remote sessionincluding a second remote session identification; transmitting a secondexecution request to the second deployment to execute a second task, thesecond execution request including the second remote sessionidentification; and receiving a second result in response to the secondexecution request, the second result being generated in the seconddeployment using a second proxy user associated with the globalidentity.
 16. The non-transitory computer readable storage media ofclaim 15, further comprising: combining the first and second results togenerate a final result.
 17. The non-transitory computer readablestorage media of claim 15, further comprising: authenticating a one-waytrust relationship associated with the global identity, wherein thesingle login session provides access to the plurality of accountswithout further authentication.
 18. The non-transitory computer readablestorage media of claim 17, wherein the authenticating is performed usinga single sign-on token.
 19. The non-transitory computer readable storagemedia of claim 15, further comprising: providing a session pool ofactive remote sessions in parallel allowing switching by the globalidentity between the active remote sessions.
 20. The non-transitorycomputer readable storage media of claim 15, wherein at least oneproperty value of the first proxy user indicates that that the firstproxy user is standing in for the global identity.
 21. Thenon-transitory computer readable storage media of claim 15, whereinreceiving the first result includes retrieving the first result from acloud storage location.